Jonathan Salinas is a Master in Computer Science with a specialization in Machine Learning from the Georgia Institute of Technology. With an E.I.T. certification in the state of Texas, Salinas has amassed experience in C/C++/Python programming languages and software systems development. He has developed and put into production machine learning tasks such as Expectation Maximization and worked with open-source ML perception tools like YOLO, detectron, and HD3. Salinas is familiar with laboratory and software documentation, personal research design journaling, and memorandum style report write-ups. His expertise in software design, Unix, MS Office, MATLAB/Simulink, and the Git version control system makes him adaptable to other programming languages such as Java, C#, Rust, and Julia.

Salinas gained experience as a Controls and Robotics Laboratory RA at the University of Texas - Pan American and was a UROP at the MIT Media Lab. He also previously worked as a Software Engineer at National Oilwell Varco and is currently a Robotic Systems Engineer at Houston Mechatronics, Inc. Salinas is well-versed in Robot Operating Systems (ROS/ROS2) and colcon/catkin CMake-based build systems. With hands-on experience on Beckhoff TwinCAT PLC's and open source and RTI's Data Distribution Services (DDS) implementations, his mathematics skillset is applied in his programming endeavors.